Towards enhancing emotional responses to media using auto-calibrating electric muscle stimulation (EMS)

Takashi Goto; Benjamin Tag; Kai Steven Kunze; Tilman Dingler

doi:10.1145/3174910.3174939

Towards enhancing emotional responses to media using auto-calibrating electric muscle stimulation (EMS)

Takashi Goto, Benjamin Tag, Kai Steven Kunze, Tilman Dingler

Graduate School of Media Design

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

We evaluate the use of Electric Muscle Stimulation (EMS) as a method of amplifying emotional responses to multimedia content. .is paper presents an auto-calibration method to stimulate two facial expressions using EMS. We focus on two expressions: frown and smile. We a.empted control of facial muscles with facial feedback for automatically calibrating these facial expressions: our computer vision system detects the facial expression and autocalibrates the EMS parameters (intensity and duration) based on the user's current facial expression. We present results from a pilot study with four participants evaluating the auto-calibration system and collecting initial feedback on the use of EMS to augment, for example, media experiences: while watching movies we can enhance the emotional response of the users during happy and sad scenes by stimulating corresponding face muscles.

Original language	English
Title of host publication	Proceedings of the 9th Augmented Human International Conference, AH 2018
Publisher	Association for Computing Machinery
Volume	Part F134484
ISBN (Electronic)	9781450354158
DOIs	https://doi.org/10.1145/3174910.3174939
Publication status	Published - 2018 Feb 6
Event	9th Augmented Human International Conference, AH 2018 - Seoul, Korea, Republic of Duration: 2018 Feb 7 → 2018 Feb 9

Other

Other	9th Augmented Human International Conference, AH 2018
Country/Territory	Korea, Republic of
City	Seoul
Period	18/2/7 → 18/2/9

Keywords

A.ective computing
Electrical Muscle Stimulation (EMS)
Emotion
Facial feedback

ASJC Scopus subject areas

Human-Computer Interaction
Computer Networks and Communications
Computer Vision and Pattern Recognition
Software

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10.1145/3174910.3174939

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Towards enhancing emotional responses to media using auto-calibrating electric muscle stimulation (EMS). / Goto, Takashi; Tag, Benjamin; Kunze, Kai Steven et al.

Proceedings of the 9th Augmented Human International Conference, AH 2018. Vol. Part F134484 Association for Computing Machinery, 2018. a29.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Goto, T, Tag, B, Kunze, KS & Dingler, T 2018, Towards enhancing emotional responses to media using auto-calibrating electric muscle stimulation (EMS). in Proceedings of the 9th Augmented Human International Conference, AH 2018. vol. Part F134484, a29, Association for Computing Machinery, 9th Augmented Human International Conference, AH 2018, Seoul, Korea, Republic of, 18/2/7. https://doi.org/10.1145/3174910.3174939

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abstract = "We evaluate the use of Electric Muscle Stimulation (EMS) as a method of amplifying emotional responses to multimedia content. .is paper presents an auto-calibration method to stimulate two facial expressions using EMS. We focus on two expressions: frown and smile. We a.empted control of facial muscles with facial feedback for automatically calibrating these facial expressions: our computer vision system detects the facial expression and autocalibrates the EMS parameters (intensity and duration) based on the user's current facial expression. We present results from a pilot study with four participants evaluating the auto-calibration system and collecting initial feedback on the use of EMS to augment, for example, media experiences: while watching movies we can enhance the emotional response of the users during happy and sad scenes by stimulating corresponding face muscles.",

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AB - We evaluate the use of Electric Muscle Stimulation (EMS) as a method of amplifying emotional responses to multimedia content. .is paper presents an auto-calibration method to stimulate two facial expressions using EMS. We focus on two expressions: frown and smile. We a.empted control of facial muscles with facial feedback for automatically calibrating these facial expressions: our computer vision system detects the facial expression and autocalibrates the EMS parameters (intensity and duration) based on the user's current facial expression. We present results from a pilot study with four participants evaluating the auto-calibration system and collecting initial feedback on the use of EMS to augment, for example, media experiences: while watching movies we can enhance the emotional response of the users during happy and sad scenes by stimulating corresponding face muscles.

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Towards enhancing emotional responses to media using auto-calibrating electric muscle stimulation (EMS)

Abstract

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Keywords

ASJC Scopus subject areas

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